Estimation of heat transfer in oscillating annular flow using artifical neural networks
Yükleniyor...
Dosyalar
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, the prediction of heat transfer from a surface having constant heat flux subjected to oscillating annular flow is investigated using artificial neural networks (ANNs). An experimental study is carried out to estimate the heat transfer characteristics as a function of some input parameters, namely frequency, amplitude, heat flux and filling heights. In the experiments, a piston cylinder mechanism is used to generate an oscillating flow in a liquid column at certain frequency and amplitude. The cycle-averaged values are considered in the calculation of heat transfer using the control volume approach. An experimentally evaluated data set is prepared to be processed with the use of neural networks. Back propagation algorithm, the most common learning method for ANNs, is used for training and testing the network. Results of the experiments and the ANN are in close agreements with errors less than 5%. The study showed that the ANNs could be used effectively for modeling oscillating flow heat transfer in a vertical annular duct. (C) 2009 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Artificial Neural Network, Oscillating Flow, Heat Transfer, Annular Duct
Kaynak
Advances in Engineering Software
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
40
Sayı
9
